Income Inequalities in Health: A Latent Class Growth Mixture Model Approach

Wednesday, 18 July 2018: 15:50
Oral Presentation
Andreea MOLDOVAN, University of Essex, United Kingdom
Michaela BENZEVAL, University of Essex, United Kingdom
Paul CLARKE, University of Essex, United Kingdom
Some of the difficulties in studying income inequalities in health have arisen from the scarcity of longitudinal data, objective measures of health, and not having the entire distribution of income available to explore the full spectrum of the relationship. Our paper contributes to the income-health gradient literature by exploring the association of long-term income trajectories and health in a different, and potentially more robust, manner to the traditional variation around the mean approach. Using data from the British Household Panel Study and the UK Household Longitudinal Study (UKHLS), we explore the full distribution of income, and model unobserved heterogeneity in income trajectories over the course of eighteen years (BHPS waves 1-18), using latent class growth mixture models (LCGMM). We adjust trajectories for age, household type, employment status, and education at baseline, year nine, and year eighteen, respectively. We find evidence of five types of income trajectories: high-increasing-plateau, high-decreasing, medium-stable, medium-increasing, and low-stable. We then investigate associations with these trajectories and: i) a range of nurse assessment measures, and ii) blood-based biomarkers collected at Wave 3 of UKHLS. We examine different pathways between long-term income and biomarkers capturing different physiological systems. Finally, we also conduct a sensitivity analysis relating mean income over 18 years to the objective health measures to assess whether a different picture of the relationship between long-term income and health emerges. Advantages and disadvantages of both approaches will be discussed. Policy implications will also be touched upon.